The spread of COVID-19 has resulted in major consequences, leaving indelible marks in several industries. The hospitality sector (hotels, restaurants, travel) is one of the industries that was most severely impacted by COVID-19 in 2020. McKinsey has developed a model that predicts a global cumulative reduction of 3 to 8 trillion USD before we return to pre-pandemic levels.
We don’t know when travel will recover, and it is difficult to predict the extent of this recovery when it does happen. Many pundits believe recreational travel will return to previous levels, while business travel will not owing to the swift technological development of the past year. What we can see is that it is in fact technology that has brought us together this past year, both at work and in the private sphere.
For travel agents, hotels and even restaurants, data is the key to understanding customers’ behavioural patterns, and at the time of writing data is also used to predict how this behaviour will change after the COVID-19 pandemic.
We do not yet know the future of the hospitality sector, but one example of what we can do today is to use the data that is already available and to optimise our decisions on the basis of this data.
Two components in the field of Data Science that are already highly developed in the hotel and travel sectors and that will have to make more progress towards more data-driven operation are AI (artificial intelligence in the form of Machine Learning) and IoT.
AI – This is what currently determines Revenue Management in the hospitality industry, with travel companies using AI to maximise their income and identify travel patterns. This is done by examining historical data and also through predictive analysis. Hotels currently have enormous quantities of data from their guests, from booking data and PR campaigns, but without AI application, development and understanding this rich data resource will not be able to be exploited to its full potential.
IoT – What is certain is that the next “normal” will be characterised by structural changes, in particular relating to travellers’ expectations regarding hygiene, flexibility, safety and security. In Singapore the government has developed the handy SafeEntry App which creates a digital diary for each passenger’s travels and visited destinations by scanning a QR code. This helps create a sense of security for the entire sector and is a goldmine packed with information and data.
The hotel sector was previously a “high-tech, high-touch” environment but it has now transitioned into a “high-tech, no-touch” environment, with features such as sensors integrated into the rooms and self-check-in systems for hotel guests. These solutions minimise contact with staff and objects, in line with the hygiene and flexibility requirements expected from tomorrow’s post-COVID-19 travellers.
Transforming an environment to “no-touch” is not as easy as it may sound; it’s not just the technology that has to be developed – even we human beings need to be trained in this new way of thinking and living. The roles of hotel employees will switch from interacting with things physically, to knowing how to perform their tasks digitally. This is a change that is currently under way and is already accelerating owing to COVID-19.
Last but not least, I predict that Data Literacy will play a vital role in the hospitality industry’s ability to absorb this development. Data Literacy is “the ability to read, write and communicate data in a given context” in order to take the next step towards a more data-driven organisation.
Will the hospitality industry understand how COVID-19 has actually impacted travellers’ future attitude to travel and the demands that will be imposed? Is the industry as a whole prepared to change many of the work-roles that today are not data-driven so that they become driven primarily by available data? How quickly can the hospitality sector – one of the world’s biggest industries – implement the measures that are necessary to return to pre-COVID-19 turnover levels with the help of Data Literacy? These are examples of the questions that all of us who enjoy working with data will doubtless be spending a lot of time examining far into the future.
Don’t hesitate to contact me since I’m very interested in hearing your thoughts and ideas on this subject. And of course you can also get in touch if you want to discuss any of the issues brought up in this blog post.